权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Statistical methodology in the health sciences

健康科学中的统计方法

基本信息

批准号：
8578-2011
负责人：
Donner, Allan
金额：
$ 1.17万
依托单位：
University of Western Ontario
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2015
资助国家：
加拿大
起止时间：
2015-01-01 至 2016-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=568605
关键词：
Statistical methodology health sciences

项目摘要

The principal objective of my research is to develop and evaluate statistical methodology that may be usefully applied to health sciences research. Most of this research involves the development of methods that may be applied when standard statistical techniques are inappropriate, due to the violation of underlying assumptions. An example of this is my past and continuing research on methods of analysis for cluster randomization trials which allocate intact social units rather than individuals to treatment. Since individuals within a cluster cannot be regarded as statistically independent, standard methods of analysis do not apply, and could result in misleading conclusions. Much of my research in this area has been focused on the development of methods that take into account within-cluster dependencies in such a way that the resulting inferences have valid and efficient statistical properties. My textbook "Design and Analysis of Cluster Randomization Trials", co-authored with Neil Klar (Arnold Publishing Co., 2000) presents a comprehensive treatment of this subject.The Chinese translated edition of this text was published in 2006. A second example involves the development of inference methods for interobserver agreement in samples of small to moderate size. Although the kappa statistics is widely used in both psychology and the health sciences to measure interobserver agreement, traditional methods for significance-testing and confidence interval construction require sample sizes that are frequently beyond the range available to many investigators. My overall objective here has been to develop a unified framework for inferences concerning interobserver agreement that accommodates both multiple raters and multiple outcome categories. Virtually all the problems I address emanate from my experience as a biostatistician collaborating with researchers in the Health Sciences.

我研究的主要目标是开发和评估可有效应用于健康科学研究的统计方法。大多数研究涉及开发当标准统计技术由于违反基本假设而不合适时可以应用的方法。这方面的一个例子是我过去和正在进行的对整群随机试验分析方法的研究，该试验将完整的社会单位而不是个人分配给治疗。由于簇内的个体不能被视为统计上独立的，因此标准分析方法不适用，并且可能导致误导性的结论。我在该领域的大部分研究都集中在开发考虑集群内依赖性的方法，从而使所得推论具有有效且高效的统计特性。我与 Neil Klar 合着的教科书《整群随机化试验的设计与分析》（Arnold Publishing Co., 2000）对这一主题进行了全面的论述。该文本的中文译本于 2006 年出版。第二个例子涉及开发中小型样本中观察者间一致性的推理方法。尽管卡帕统计在心理学和健康科学中广泛用于测量观察者间的一致性，但用于显着性检验和置信区间构建的传统方法所需的样本量常常超出许多研究人员可用的范围。我的总体目标是开发一个统一的框架，用于有关观察者间一致性的推论，以适应多个评估者和多个结果类别。事实上，我解决的所有问题都源于我作为生物统计学家与健康科学研究人员合作的经验。